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Mechanistic Insights into Tacrine Binding to Acetylcholinesterase in Alzheimer’s Disease from Molecular Docking and Molecular Dynamics Simulations

This study utilizes molecular docking and 100 ns molecular dynamics simulations to demonstrate that tacrine stably binds to the active site of acetylcholinesterase (PDB ID: 1EVE) primarily through $\pi$ – $\pi$ stacking interactions with key aromatic residues, providing mechanistic insights for designing improved Alzheimer's disease therapeutics.

Original authors: Saheen Shehnaz Begum, Trinayan Dulakakharia, Srutishree Sarma

Published 2026-10-13

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CC BY 4.0

Original authors: Saheen Shehnaz Begum, Trinayan Dulakakharia, Srutishree Sarma

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

Alzheimer's disease is a relentless thief of memory, slowly eroding the ability to think, learn, and recognize the world. At the heart of this condition lies a breakdown in the brain's chemical messaging system, specifically involving a vital neurotransmitter called acetylcholine. This molecule acts as a spark for communication between nerve cells, but an enzyme known as acetylcholinesterase is tasked with breaking it down after use. In a healthy brain, this cycle maintains a delicate balance, but in Alzheimer's, the loss of acetylcholine contributes to the cognitive decline that defines the illness. To slow this progression, scientists have long sought ways to block that enzyme, effectively keeping more acetylcholine available to keep the brain's circuits firing. One of the earliest and most famous compounds to do this is a drug called tacrine. Although it is no longer prescribed due to side effects, it remains a crucial reference point for researchers, a known quantity that helps them understand how to design better, safer medicines.

In a recent study, researchers turned to the power of computer simulation to look inside the invisible world where drugs meet proteins. Instead of mixing chemicals in a test tube, they built a digital model of the acetylcholinesterase enzyme and the tacrine molecule to watch how they interact. Using a method called molecular docking, they essentially tried to fit the tacrine molecule into the enzyme's active site, the specific pocket where the chemical work happens. The computer calculated how well the two shapes fit together and how strongly they would hold on to one another. The results showed that tacrine fits snugly into the enzyme's cavity, forming a stable connection with a binding energy of −7.17 kcal/mol. This negative value indicates a strong, favorable attraction, suggesting that the drug naturally seeks out and settles into the enzyme's grip.

To ensure this fit was not just a lucky snapshot but a lasting relationship, the scientists ran a virtual experiment that played out over time. They subjected the locked-together pair to a molecular dynamics simulation, a process that mimics the constant jiggling and movement of molecules in a living body. For 100 nanoseconds—a blink of an eye in human time but an eternity in the molecular world—the computer tracked every movement of the protein and the drug. Throughout this period, the enzyme remained structurally sound, maintaining its shape without unraveling or collapsing. The tacrine molecule, meanwhile, stayed firmly anchored within the active site, never drifting away. The simulation revealed that the bond was held together not by a single force, but by a network of interactions. The most important of these were stacking interactions between the flat, ring-like structures of the drug and specific aromatic amino acids in the enzyme, such as Trp84, Tyr121, and Phe330. These aromatic rings act like flat tiles that slide against one another, providing a stable foundation.

Beyond these primary anchors, the drug also relied on a web of weaker connections to stay in place. Hydrophobic interactions, where non-water-loving parts of the molecule cluster together, and fleeting hydrogen bonds helped secure the drug's orientation. The computer analysis showed that while the enzyme's outer loops moved and flexed naturally, the core region where the drug sat remained rigid and unchanging. The drug adjusted slightly during the first moments of the simulation to find its perfect position, but once settled, it remained there for the duration of the run. This stability suggests that the way tacrine binds is robust and predictable, relying on a cooperative network of forces that keep it locked in the enzyme's grip.

The study confirms that tacrine forms a durable complex with acetylcholinesterase, held together by a specific arrangement of aromatic stacking and hydrophobic contacts. While the drug itself is no longer used in clinics, understanding exactly how it holds on provides a clear blueprint for the future. By seeing which parts of the enzyme are essential for holding the drug, researchers can now design new molecules that might stick even tighter or avoid the toxic side effects that plagued the original compound. This work does not offer a new cure, but it offers a precise map of the molecular landscape, showing exactly where the pieces fit and how they stay together. In the quiet, invisible theater of the cell, the dance of molecules is governed by these specific, physical rules, and this study has simply made those rules visible.

Technical Summary: Mechanistic Insights into Tacrine Binding to Acetylcholinesterase

Problem Statement
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory loss and cognitive decline, placing a significant global burden on healthcare systems. A primary pathological feature involves the accumulation of amyloid-β plaques and neurofibrillary tangles, leading to synaptic dysfunction. While no current therapy halts disease progression, Acetylcholinesterase (AChE) inhibition remains a standard symptomatic treatment to increase acetylcholine levels in the brain. Tacrine (1,2,3,4-tetrahydroacridin-9-amine) was the first AChE inhibitor approved for AD but was discontinued due to hepatotoxicity. Despite this, it serves as a critical reference compound for understanding AChE inhibition. The study aims to elucidate the molecular mechanisms of tacrine binding to human AChE (PDB ID: 1EVE) to inform the rational design of improved, less toxic inhibitors.

Methodology
The study employed an integrated computational approach comprising three stages:

Geometry Optimization: The tacrine molecule (C13H14N2) was optimized using Density Functional Theory (DFT) via the Gaussian 09 software package. The B3LYP functional with the 3-11G basis set was utilized to determine the stable molecular geometry, bond lengths, and bond angles.
Molecular Docking: The DFT-optimized tacrine structure was docked into the active site of the AChE crystal structure (1EVE) using AutoDock 4.2. A blind docking strategy was employed with a grid box of 126 × 126 × 126 points to explore the entire receptor surface. The Lamarckian Genetic Algorithm performed 10 independent runs with 2,500,000 energy evaluations each to identify the most favorable binding poses.
Molecular Dynamics (MD) Simulations: The best-docked tacrine-AChE complex underwent a 100 ns MD simulation using GROMACS 5.1.2 with the OPLS-AA all-atom force field. The system was solvated with explicit SPC/E water molecules and neutralized with counterions. Following energy minimization and equilibration at 298 K and 1 bar, a production run was executed. Structural stability and interaction dynamics were analyzed using Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and Radius of Gyration (Rg).

Key Results

Docking Analysis: Tacrine exhibited a favorable binding affinity with a binding energy of −7.17 kcal/mol and an estimated inhibition constant ( $K_i$ ) of 5.59 μM. The binding was primarily driven by van der Waals interactions, hydrogen bonding, and desolvation effects (−7.40 kcal/mol), with minimal electrostatic contribution (−0.06 kcal/mol). The ligand occupied the active-site gorge, forming a stable complex.
Interaction Mechanism: The stability of the complex was largely attributed to strong $\pi$ – $\pi$ stacking interactions between the tacrine aromatic rings and key aromatic residues: Trp84, Tyr121, Tyr334, and Phe330. Additional stabilization was provided by hydrophobic contacts and transient hydrogen bonds with residues such as Gln69, Ser122, and Tyr334.
MD Simulation Stability: Over the 100 ns trajectory, the protein-ligand complex demonstrated high structural stability.
- RMSD: The protein backbone remained stable with fluctuations between 0.15 and 0.22 nm. The ligand showed initial adjustment (0.50–0.60 nm) before stabilizing, indicating it remained confined within the active site without dissociation.
- RMSF: Most residues showed low flexibility (0.05–0.15 nm). Higher fluctuations were restricted to loop regions and terminal residues, while the binding pocket residues remained rigid, preserving the interaction network.
- Radius of Gyration (Rg): The Rg profile remained constant, confirming that the protein maintained its compact tertiary structure and did not undergo unfolding or significant expansion.

Significance and Claims
The paper claims that the integrated computational workflow successfully validates the stability of the tacrine-AChE complex under dynamic conditions. The study highlights that the binding mechanism is governed by a cooperative network of aromatic $\pi$ – $\pi$ stacking, hydrophobic contacts, and transient hydrogen bonds. The authors assert that these findings provide molecular-level insights into the binding mode of tacrine, reinforcing the role of aromatic residues in ligand recognition. While acknowledging tacrine's historical limitations, the paper posits that understanding these specific interaction patterns contributes to the rational design and optimization of future acetylcholinesterase inhibitors with improved therapeutic potential for Alzheimer's disease. The study emphasizes the utility of combining DFT, docking, and MD simulations as a robust framework for investigating protein-ligand interactions.

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